Analysis of chemical contamination by hazardous drugs with BD HD Check® system in a tertiary hospital

The presence of contamination in the healthcare work environment by one of the types of hazardous drugs, cytostatics, has been found in multiple international studies. Recent studies and guidelines recommend surface monitoring for risk assessment of healthcare professionals’ exposure. The availability of detection techniques is critical to successfully carry out this type of monitoring. The use of new semi-quantitative techniques allows quicker results. The main objective of this study was to determine the existence of hazardous drugs on the working surfaces in different locations of a tertiary hospital using the BD HD Check® semi-quantitative device. The presence of methotrexate, doxorubicin and cyclophosphamide was analysed at 80, 89 and 82 locations in 10, 13 and 11 clinical units, respectively. A total of 251 samples were analysed. The monitoring results were positive for 13.1% of the analysed samples, with 36.3% of the methotrexate samples, 0% of the doxorubicin samples and 4.9% of the cyclophosphamide samples. Mapping the presence of HD in our hospital has allowed us to evaluate the effectiveness of controls established in the hospital to minimise the exposure of healthcare professionals to hazardous drugs. The speed in obtaining results has enabled immediate corrective actions in cases where contaminated surfaces were detected.

Joint microseismic moment tensor inversion and location using P- and S-waves diffraction stacking

The microseismic location methods based on diffraction stacking which does not require arrival picking can yield accurate and reliable source location for data with a low signal-to-noise ratio. However, due to the complex radiation pattern from a rupturing source, variation in the waveform polarities brings challenges to the diffraction-stacking based methods. The current implementations of joint source mechanism inversion and location methods which only use P-wave amplitudes have limitations in noise resistance and location accuracy. To mitigate those issues, we develop a new method for joint microseismic moment tensor inversion and event location using diffraction stacking with P- and S-waves amplitudes, both of which are used to invert for the moment tensor of a microseismic event, and then the inverted moment tensor is used to correct the waveform polarity changes before stacking. In addition, to expedite the large amount of calculations required for moment tensor inversion at each potential source position and origin time, we develop an optimized grid search scheme and implement the algorithm with GPUs. The proposed location method does not require manual picking of the first arrivals, and can automatically detect and locate microseismic events from continuous data. We first validated the method with two synthetic examples, and then applied it to a surface monitoring dataset for hydraulic fracturing at a shale gas well pad in the southern Sichuan Basin, China, where billions of cubic meters of shale gas are being produced annually. The locations of the microseismic events are nicely correlated with the fracturing stages and the determined source mechanisms are also consistent with the expected fracture growth. The proposed method is feasible for microseismic surface monitoring with dense nodal arrays and can provide important information for fracture growth and regional stress characterization.

Innovative Non-Irradiating and Non-Invasive Per Fraction Control System in Radiotherapy: Surface-Guided Radiation Therapy Experience of Casablanca Cancer Center

Purpose: Evaluation of the added value of radiotherapy guided by the cutaneous surface in the positioning and monitoring of the radiotherapy Patients and Methods: This study included 21 consecutive patients treated with an accelerator dedicated to "True Beam®" stereotactic radiotherapy whose sessions were monitored by an Optical Surface Monitoring System: "OSMS®". Excluded from our study were treatments controlled exclusively by radiological imaging (IGRT). Positioning variabilities were compared between conventional imaging and skin surface infrared (OSMS) monitoring. Conventional imaging was in the form of standard radiography (KV) performed during the treatment session or three- dimensional by a series of Cone Beam computerized tomography (CBCT) scanned images made at the beginning and end of The total time of the session and the positioning variability’s in the 3 planes were 14 Results: The results of our study show that the cutaneous surface monitoring allowed to obtain a faster alignment of the patient with an improvement in the overall time of the session with a mean at 32% [14.5-49.27%], likewise a sub-millimeter positioning quality for all locations with a median longitudinal distance of 0.02 cm [0-0.66], 01 cm verticality [0-0.32] and laterality 0.02 cm [0-0.77] This benefit is significantly greater for cerebral and Head and neck’s localizations 21 Conclusion: Optical Surface Monitoring System (OSMS®) is a non-invasive and non- irradiating means that allows reliable and fast

DESCRIPCIÓN DEL PROYECTO DE TESIS DOCTORAL: APLICACIÓN DE LA TECNOLOGIA DINSAR A LA PREVENCION DE LOS RIESGOS GEOLOGICOS NATURALES E INDUCIDOS EN CIUDADES E INFRAESTRUCTURAS PRIORITARIAS DE CENTROAMÉRICA

Este documento presenta la formulación y primeros pasos de un proyecto de Doctorado Industrial, desarrollado en elmarco del proyecto Kuk ahpán que tiene como objetivo comprender, monitorear y modelar procesos tectónicos a escalalitosférica en Centroamérica. Para ello, un equipo internacional de seis países (Nicaragua, Costa Rica, El Salvador,Guatemala, Noruega y España) trabaja integrando la investigación en diversas técnicas e ingenierías Geofísicas, con elobjetivo de actualizar los Mapas de Riesgo Sísmico de la Región, un insumo crítico. para los códigos de seguridad yconstrucción. El proyecto de doctorado propuesto se enmarca en la investigación y desarrollo de tecnologías para prevenirlos riesgos geológicos naturales e inducidos que afectan a ciudades e infraestructuras en países altamente vulnerables,utilizando la tecnología DInSAR (Differential Interferometry with Synthetic Aperture Radar) optimizada por la startupDetektia Earth Surface Monitoring en colaboración con la Universidad Politécnica de Madrid. La interferometría diferencialde radar de apertura sintética es una técnica basada en el procesamiento y análisis de series largas de imágenes de radarde apertura sintética. Esta tecnología proporciona registros (desde 1992) y movimientos actualizados en cualquiersuperficie en cualquier parte del mundo sin necesidad de instrumentación terrestre, con precisiones de alrededor de 1 mm/ año (velocidad). En este contexto, el radar satelital proporciona información valiosa sobre áreas muy grandes quecomplementan el trabajo de campo y la instrumentación in situ. Primero, comenzamos integrando datos DInSAR condiversos datos geofísicos como batimetría, geomagnetismo, gravimetría, perfiles sísmicos… para mapear completamentela falla Swan sobre Honduras y Guatemala. Usamos esta tecnología para abordar el riesgo sísmico sobre la falla y áreascercanas. En un segundo paso, aplicaremos esta evaluación de riesgo sísmico (incluyendo amenazas naturales yantropogénicas) en ciudades e infraestructuras críticas en Centroamérica.

A Crowdsourcing Technique For Road Surface Monitoring Using Smarthphone Sensors

Road surface monitoring is a key factor in providing safe road infrastructure for road users. As a result, road surface condition monitoring aims to detect road surface anomalies such potholes, cracks and bumps, which affect driving comfort and on-road safety. Road surface anomaly detection is a widely studied problem. Recently, smartphone-based sensing has become popular with the increased amount of available embedded smartphone sensors. Using smartphones to detect road surface anomalies could change the way government agencies monitor and plan for road rehabilitation and maintenance. Several studies have been developed to utilize smartphone sensors (e.g., Global Positioning system (GPS) and accelerometers) mounted on a moving vehicle to collect and process the data to monitor and tag roadway surface defects. Geotagged images or videos from the roadways have also been used to detect the road surface anomalies. However, existing studies are limited to identifying roadway anomalies mainly from a single source or lack the utility of combined and integrated multi-sensors in terms of accuracy and functionality. Therefore, low-cost, more efficient pavement evaluation technologies and a centralized information system are necessary to provide the most up-to-date information about the road status due to the dynamic changes on the road surface This information will assist transportation authorities to monitor and enhance the road surface condition. In this research, a probabilistic-based crowdsourcing technique is developed to detect road surface anomalies from smartphone sensors such as linear accelerometers, gyroscopes and GPS to integrate multiple detections accurately. All case studies from the proposed detection approach showed an approximate 80% detection accuracy (from a single survey) which supports the inclusiveness of the detection approach. In addition, the results of the proposed probabilistic-based integration approach indicated that the detection accuracy can be further improved by 5 to 20% with multiple detections conducted by the same vehicle along the same road segments. Finally, the development of the web-based Geographic Information System (GIS) platform would facilitate the real-time and active monitoring of road surface anomalies and offer further improvement of road surface quality control in large cities like Toronto.